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Auxiliary Learning

Auxiliary learning aims to find or design auxiliary tasks which can improve the performance on one or some primary tasks.

( Image credit: Self-Supervised Generalisation with Meta Auxiliary Learning )

Papers

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Showing 31–40 of 100 papers

TitleStatusHype
Multi-task Collaborative Pre-training and Individual-adaptive-tokens Fine-tuning: A Unified Framework for Brain Representation Learning—0
Bootstrapped Representations in Reinforcement Learning—0
LitCall: Learning Implicit Topology for CNN-based Aortic Landmark Localization—0
Meta-Auxiliary Learning for Adaptive Human Pose Prediction—0
Learning to Recover Spectral Reflectance from RGB ImagesCode1
MELTR: Meta Loss Transformer for Learning to Fine-tune Video Foundation ModelsCode1
Introducing Depth into Transformer-based 3D Object Detection—0
Unified Convergence Theory of Stochastic and Variance-Reduced Cubic Newton Methods—0
Enhancing Deep Knowledge Tracing with Auxiliary TasksCode0
Auxiliary Learning as an Asymmetric Bargaining GameCode1
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